Intention is choice with commitment
Artificial Intelligence
Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity)
Loss Aversion Under Prospect Theory: A Parameter-Free Measurement
Management Science
Dynamic Control of Intention Priorities of Human-like Agents
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Emergence of norms through social learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Topology and Memory Effect on Convention Emergence
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Dynamic sanctioning for robust and cost-efficient norm compliance
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Open issues for normative multi-agent systems
AI Communications
Norms and learning in probabilistic logic-based agents
DEON'12 Proceedings of the 11th international conference on Deontic Logic in Computer Science
Human-inspired model for norm compliance decision making
Information Sciences: an International Journal
Social norms for self-policing multi-agent systems and virtual societies (extended abstract)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Internalization is at study in social-behavioural sciences and moral philosophy since long; of late, the debate was revamped within the rationality approach to the study of cooperation and compliance since internalization is a less costly and more reliable enforcement system than social control. But how does it work? So far, poor attention was paid to the mental underpinnings of internalization. This paper advocates a rich cognitive model of different types, degrees and factors of internalization. In order to check the individual and social effect of internalization, we have adapted an existing agent architecture, EMIL-A, providing it with internalization capabilities, turning it into EMIL-I-A. Experiments have proven satisfactory results with respect to the maintenance of cooperation in a proof-of-concept simulation.